Detection Of Lard Research Articles

Detection of Lard in Animal Fat Mixtures Using ATR-FTIR Fingerprint and SPME-GC/MS-Based Volatilomics

This study aims to detect the presence of lard in several halal animal fats (beef, chicken, and goat fat) based on their infrared fingerprint and volatile compound profile (volatilomics). A mixture of fat samples obtained from halal animals and lard at different concentrations (0, 20, 40, 60, and 80%, v/v) were subjected to attenuated total reflection-Fourier transformed infrared spectroscopy (ATR-FTIR) and solid phase microextraction coupled to gas chromatography-mass spectrometry (SPME-GC/MS) analysis, respectively. The data was processed using orthogonal projection to the least square–discriminant analysis (OPLS-DA). The results showed that ATR-FTIR could only identify the presence of lard in chicken fat up to the lowest concentration used in this study (10%) but failed in other fat samples. SPME-GC/MS detected the presence of lard in all animal fats up to the lowest concentration added (10%). The results of this study revealed that the volatilomics technique had more potential to be developed as a basis for the rapid detection of halal and non-halal animal fat than the infrared fingerprint. This study also emphasized that markers of non-halal animal fats can be different when the same fats are added to different food products.

IDENTIFICATION OF LARD ON PROCESSED PRODUCTS IN MEDAN CITY USING UV SPECTROPHOTOMETER WITH LINEAR DISCRIMINANT ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS METHODS

Objective: Processed meat products are highly popular among the community. However, deceptive traders sometimes adulterate these products with pork elements, necessitating thorough inspections. The qualitative detection of lard in processed products can be analyzed using UV spectrophotometry with chemometric techniques such as Linear Discriminant Analysis and Principal Component Analysis. These methods facilitate data analysis derived from spectra and wavelengths, enabling the categorization of objects and providing high accuracy.
 Methods: This study aimed to determine whether processed products in Medan contain lard using UV spectrophotometry, Linear Discriminant Analysis, and Principal Component Analysis methods.
 Results: The highest fat yield was obtained from lard at 14.24%, while the lowest was from chicken fat at 7.00%. The maximum wavelength results for control samples were 234 nm for chicken fat, 237 nm for beef fat, and 268 nm for lard. Data processing using Linear Discriminant Analysis and Principal Component Analysis showed that the processed products of three random samples, nugget, meatball, and sausage type A and C, fell within the same quadrant as chicken fat. Meatball and sausage type B were in the same quadrant as beef fat.
 Conclusion: Based on the identification of lard in processed products in Medan City using UV spectrophotometer by LDA and PCA, all random samples of nuggets, meatballs, and sausages do not contain lard, and this method can classify chicken fat, beef fat, lard well.

A conjunction of sn-2 fatty acids and overall fatty acid composition combined with chemometric techniques increase the effectiveness of lard detection in fish feed

Fish oil is a common source of fat in fish feed production. However, there is a tendency to substitute fish oil with other fats such as lard to reduce production costs. Thus, an efficient method for lard detection is highly needed for fish feed’s authenticity. In this study, sn-2 fatty acids (sn-2 FAs) and fatty acid (FA) compositions were incorporated with chemometric techniques namely Principal Component Analysis (PCA), Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA), and Orthogonal Partial Least Square-Regression (OPLS-R) to identify lard adulteration in the fish feeds. The inclusion of sn-2 FAs into PCA model 2 exhibited a preferable variation pattern relative to PCA model 1. The PCA identified C14:0, C18:0, C18:2, C18:3, C20:0 sn-2 C16:0, sn-2 C18:0, sn-2 C18:1, and sn-2 C18:2 were the most significant FAs to discriminate the fish feeds. The inclusion of sn-2 FA composition improved the OPLS-DA model 2 performance by providing more significant class discrimination between lard-adulterated, and non-adulterated fish feeds as compared to OPLS-DA model 1. The OPLS-DA model 2 identified C18:0, C18:2, C18:3, and sn-2 C16:0 FAs as markers of lard adulteration with an increment in the value of the coefficient of determination (R2) and decrement in the Root Mean Square Error of Estimation (RMSEE) and Root Mean Standard of Cross-Validation (RMSECV) values. The Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron-Artificial Neural Network (MLP-ANN), and internal and external validations corroborated the OPLS-DA model 2 and OPLS-R model 2 performances. Therefore, the incorporation of sn-2 FA and FA compositions coupled with the chemometric techniques had improved the detection and quantification of lard adulteration in fish feeds.

Fluorescence polarization method for detection of lard mixed with olive oil

This study is based on fluorescence polarization as a potential alternative method for an investigation of contamination of lard in food. The purpose of this study was to obtain the characteristic of fluorescence polarization in olive oil samples mixed with lard. The characteristics of fluorescence polarization were obtained by measuring changes in the polarization of light using a linearly polarized green laser pointer and observed in the direction of the scattering angle of 90˚ for various direction of electric field of the laser. The results showed that the critical angle of direction of electric field of the laser and the average polarization change increase as the concentration of lard is raised. It could be due by additional asymmetric triglycerides and molecular orientation that play an important role in the sample. This result shows that additional mixture of lard in olive oil can be detected, and this method seems to be developed for the detection of low concentrations of lard contamination.

Detection of lard in butter using Raman spectroscopy combined with chemometrics.

There is a contentious need for robust and rapid methodologies for maintaining the authenticity of foods and food additives. The current paper presented a new Raman spectroscopy-based methodology for detection and quantification of lard in butter. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully performed for the classification and discrimination of butter and lard-adulterated samples. Strong discrimination pattern was observed in the HCA analysis. Also, partial least squares regression and principal component regression (R2=0.99) were applied for quantification of lard in butter samples. Quite favorable prediction capabilities were observed in the cross-validation of PLS and PCR analysis for the adulteration levels between 0% and 100% lard fat (w/w). Raman spectroscopy coupled chemometrics was employed effectively for quantification of lard fat in butter fat samples with easy, robust, effective, low-cost and reliable application in the quality control of butter.

Preliminary Immunochemical Studies to Detect Lard

Detection of lard in food using immunochemical methods has been carried out. This method has been applied and developed in food analysis. The purpose of this study was to detect the presence of lard in food. The method used was immunochemical which in this case is tested to its application in food analysis. The principle method is based on the antigen-antibody reaction, between lipids as antigens that can be deposited by antibodies in the agar medium. Antibodies were obtained by inducing lard into the blood vessels of rabbits. This method is based on the antigen-antibody reaction between fat as an antigen and antibodies that contain anti-lard as reagents and the occurrence of precipitation in agar media. The antibody was obtained by inducing lard, pork broth, and pig plasma into the blood vessels of rabbits. The results of this study were significant.

Lard detection using a tapered optical fiber sensor integrated with gold-graphene quantum dots

In this paper, we reported the detection of lard using tapered optical fiber integrated with graphene quantum dot (GQD). Two different sensors were fabricated and tested, one coated with GQD only as sensing element, the other was coated with gold (Au)-GQD to be tested with lard concentration ranging from 20% till 100%. The GQD coated sensor obtained a sensitivity of 0.034/a.u.% at fluorescence emission peak 652 nm. Meanwhile the Au-GQD sensor, obtained higher sensitivity at 0.042/a.u.% with peak fluorescence emission at 680 nm. The proposed sensor shows a great potential of using sensor in detection of lard for future advancement of food technolog.

Detection of lard contamination in five different edible oils by FT-IRspectroscopy using a partial least squares calibration model

Lard is defined as animal fat acquired from the adipose tissue of pigs and is not permitted for human consumption or external use by certain religions such as Islam and Judaism. Due to its low-cost availability for commercial use, it is often mixed with other vegetable oils mistakenly or deliberately and causes loss of consumer trust; hence, its detection in food products is essential. Consumers tend to know the authenticity of commercially available edible oils. However, edible oils are subjected to adulteration risks with lard, which breaches consumer rights. In the present study, we designed a transmission Fourier transform infrared spectroscopy (FT-IR)-based method for the rapid detection of lard in sunflower, canola, coconut, olive, and mustard oils. For this purpose, the selected oils were adulterated with lard in different concentration ratios (10:0, 9:1, 7:3, 6:4, 4:6, 3:7, 0:10). A single calibration model was developed for 35 standards (seven standards from each individual five oils) in the frequency range between 1078.01 and 1246.75 cm$^{-1}$ to determine the relationship between actual adulterant concentration and FT-IR predicted concentrations using a partial least squares (PLS) method. The results of the present study indicated that FT-IR in combination with PLS has the potential to evaluate adulteration of edible oils with lard through single calibration as a rapid, nondestructive, and effective alternative method.

Detection of Lard in Cocoa Butter-Its Fatty Acid Composition, Triacylglycerol Profiles, and Thermal Characteristics.

The present study investigates the detection of lard in cocoa butter through changes in fatty acids composition, triacylglycerols profile, and thermal characteristics. Cocoa butter was mixed with 1% to 30% (v/v) of lard and analyzed using a gas chromatography flame ionization detector, high performance liquid chromatography, and differential scanning calorimetry. The results revealed that the mixing of lard in cocoa butter showed an increased amount of oleic acid in the cocoa butter while there was a decrease in the amount of palmitic acid and stearic acids. The amount of POS, SOS, and POP also decreased with the addition of lard. A heating thermogram from the DSC analysis showed that as the concentration of lard increased from 3% to 30%, two minor peaks at −26 °C and 34.5 °C started to appear and a minor peak at 34.5 °C gradually overlapped with the neighbouring major peak. A cooling thermogram of the above adulterated cocoa butter showed a minor peak shift to a lower temperature of −36 °C to −41.5 °C. Values from this study could be used as a basis for the identification of lard from other fats in the food authentication process.

DEVELOPMENT OF LARD DETECTION IN CRUDE PALM OIL (CPO) USING FTIR COMBINED WITH CHEMOMETRICS ANALYSIS

Objective: The aim of this research to design lard detection using FTIR spectroscopy combined Partials Least Square (PLS).Methods: Development of analysis method of lard in CPO oil using FTIR combined PLS to quantification of lard in CPO oil. Data processing in this study is looking for correlation about actual value and FTIR predicted value. The good correlation will give the high R2 value and low Root Mean Square Calibration (RMSEC), and Root Mean Square error External Cross Validation (RMSECV).Results: The results showed that The analysis method using FTIR for lard detection with combination of the fingerprint spectrum at wave number 1481-999 cm-1 with wave number such as 779-650 cm-1, 1749-1650 cm-1 and 2990-3045 cm-1. This research resulted good correlation about actual value and predicted value at combination of wave number 1481.22-999.05 & 1793.67-1650.95 with R2 value is 0.998. The detection error is lowest because it has a small of RMSEC and RMSECV value with 0.998, 1.291 % (v/v), 0838% (v/v) respectively.Conclusion: The characteristic of lard in CPO oil can be detected at combination of wave number 1481.22-999.05 & 1793.67-1650.95 with R2 value is 0.998 and RMSEC and RMSECV value with 0.998, 1.291 % (v/v), 0838% (v/v) respectively.Keyword: FTIR, halal authentication, lard detection, analysis method

Application of HPLC (High Pressure Liquid Chromatography) for Analysis of Lard in the Meatball Product Combined with PCA (Principal Component Analysis)

Meatball is favorite food for Indonesian society. Nowadays, many issues about the food ingredient on meatball were mixed with Lard. Therefore, this study was focused on applications of HPLC UV for the lard detection in meatball. The results showed that the beef and pork meatball can be distinguished using HPLC which was combined Principal Component Analysis (PCA). However, the application of HPLC has a problem for lard detection in meatball because can’t to control the hydrolysis of triglyceride (TGA). Hydrolysis of triglycerides can also be detected using HPLC UV and giving the interference for halal authentication.

Inhibitory Effect of Chocolate Components Toward Lard Detection in Chocolate Using Real Time PCR

An identification method of lard in chocolates using real-time polymerase chain reaction was developed to address Halal authentication. However, polymerase chain reaction detection of lard in chocolate has been in vain. In order to investigate the inhibitory effect exerted by each of the chocolate components, four basic chocolate components, sugar, milk powder, cocoa butter, and cocoa powder, were adulterated with lard and examined using porcine-specific real-time polymerase chain reaction assay. The results discovered cocoa powder, as the only component that prevents DNA extraction of lard in chocolate. No substantial polymerase chain reaction inhibition was detected, and thus confirms the cocoa powder’s inhibition on DNA extraction of lard from lard-adulterated chocolate. This finding will expedite new research to develop a method to dissociate the lard from the lard-cocoa powder complex, which will have high potential to be applied as a pre-treatment of the chocolate prior to the DNA extraction and polymerase chain reaction.

Detection of Lard in Binary Animal Fats and Vegetable Oils Mixtures and in Some Commercial Processed Foods

Detection of Lard in Binary Animal Fats and Vegetable Oils Mixtures and in Some Commercial Processed Foods

Detection of Lard in Ink Extracted from Printed Food Packaging Using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

Fourier transform infrared (FTIR) spectroscopy combined with chemometrics was utilised to discriminate the presence of lard in extracted ink of printed food packaging. Two spectral regions (full spectra, 3999–649 cm−1, and combination of two regions, 3110–2630 cm−1and 1940–649 cm−1) of lard, commercial gravure ink, and the blends of both were selected and used to develop a Soft Independent Modelling of Class Analogy (SIMCA) model. The score plots obtained from the Principal Component Analysis (PCA) revealed that the maximum number of factors (7 factors) was needed to explain 84% of the total variance. SIMCA was employed as the method to classify the samples into their specific groups.SiversusHiplots showed that the calibration standards can be classified as lard-containing standards. Sample 2 was deduced to have the highest possibility of containing lard, while only samples 5 and 7 cannot be classified as lard-containing samples. These results demonstrated that FTIR spectroscopy, when combined with multivariate analysis, can provide a rapid method with no excessive sample preparation to detect the presence of lard in ink of foodstuff packaging.

Reference Materials as a Crucial Tools for Validation and Verification of the Analytical Process

Traceability in analytical measurements is a key issue to ensure all measurement results are accurate, comparable and the products are safe for consumption. Therefore, validity of measurements can be assured when reference materials (RMs) are used to calibrate the equipments before the test report can be published. The role of reference materials in analytical process is outlined with specific example on high purity substances and validation process involved in quality assurance (QA). The main tasks of National Metrology Laboratory, SIRIM Berhad (NML-SIRIM) are reviewed including to ensure all measurement results are traceable to the international system of unit (SI), setting up the national primary standards and participating in international comparison organized by International Bureau of Weight and Measures (BIPM). Several advantages and crucial aspects for the validation of high purity organic RMs using quantitative nuclear magnetic resonance (qNMR) are discussed and illustrated by recent example for detection of lard in animal fats.

Detection of lard in vegetable oils

AbstractThe presence of animal fats, in particular lard (pig fat), in any product is of real concern to some communities, especially Muslims and Jews, due to the religious prohibition of these commodities. This is especially so when lard is used as substitute for vegetable oils in foods or other consumer goods such as cosmetics and pharmaceuticals. Manufactures and producers alike should be sensitive towards the issues of unlawful material in these products as halal and kosher markets are expected to proliferate in the coming years. This article highlights some analytical techniques proposed to detect and to quantify lard in vegetable oils such as Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), chromatographic‐based techniques, and electronic nose (EN).

Lard detection based on fatty acids profile using comprehensive gas chromatography hyphenated with time-of-flight mass spectrometry

Comprehensive gas chromatography hyphenated with time-of-flight mass spectrometry was applied to detect the differences between lard (LA) and three other commonly animal-derived fats, namely cattle fat (CA), chicken fat (CF) and goat fat (GF). Combination of two different microbore columns (SLB-5ms and DB-wax) allowed the discrimination of lard from other animal fats by three fatty acid methyl esters (FAMEs) constituents involving methyl trans-9,12,15-octadecatrienoate (C18:3 n3t), methyl 11,14,17-eicosatrienoate (C20:3 n3t) and methyl 11,14-eicosadienoate (C20:2 n6). The FAME profiles could be used as a basis for discriminating lard from other animal fats in food authentication process.

Detection of lard adulteration in RBD palm olein using an electronic nose

The use of surface acoustic wave (SAW) sensing electronic nose (zNose™) for detection of lard as an adulterant in refined, bleached, deodorized (RBD) palm olein was investigated. Mixing of animal fats, especially lard in any form in food products, is a cause of concern for certain religions. RBD palm olein spiked with lard at levels ranging from 1% to 20% (w/w) was analyzed. The zNose™ produced a two-dimensional olfactory image called VaporPrint™, which could be used for immediate detection (qualitatively) of lard substances in sample admixtures. Lard adulteration could be determined by a few distinct peaks in the zNose™ chromatogram. The best relationship between percentage of lard in adulterated RBD palm olein and SAW detector response was observed in adulterant peak E ( R 2 = 0.906). Pearson’s correlation coefficient ( r) was calculated using this parameter. An ideal correlation was observed between the zNose™ data and other chemical tests ( r > 0.90).

Lard uptake and its detection in selected food products deep-fried in lard

Analytical methods for the detection of both pork and lard in food products are in great demand for regulatory purposes. Means of identifying food products fried in lard has been investigated in this study. Four fat containing products namely, peanuts, tempeh (fermented soybean cake), chicken and beef were subjected to deep-fat frying using lard as the frying medium. Oils extracted from the control and fried samples were analyzed by gas liquid chromatography (GLC), high performance liquid chromatography (HPLC) and differential scanning calorimetry (DSC). In this way, changes in composition and thermal profiles during frying were examined. Results showed that palmitic acid enrichment factor (PAEF) calculated from GLC analysis of fatty acid methyl esters seems to be a useful parameter in determining lard contamination in all four fried products. With the triglycerol (TG) profiling by HPLC it was possible to detect lard in fried chicken and tempeh products while DSC cooling and heating traces were found to be useful for lard detection in fried tempeh, chicken and beef products.

Detection of lard and randomized lard as adulterants in refined‐bleached‐deodorized palm oil by differential scanning calorimetry

AbstractA study was conducted to assess the use of differential scanning calorimetry (DSC) for detecting the presence of lard/randomized lard as adulterants in refined‐bleached‐deodorized (RBD) palm oil. Lard extracted from the adipose tissues of pig was chemically interesterified using sodium methoxide as catalyst. DSC thermal profiles of both genuine lard and randomized lard were compared with those of other common animal fats such as beef tallow, mutton tallow, and chicken fat. Lard and randomized lard were then blended with RBD palm oil in two series, in proportions ranging from 0.2 to 20%, and DSC analyses were obtained. The DSC cooling profiles of adulterated RBD palm oil samples showed an adulteration peak corresponding to lard/randomized lard in the low‐temperature region. This peak was confirmed as an indicator of the presence of lard in RBD palm oil since similar experiments carried out using other common animal fats such as mutton tallow, beef tallow, and chicken fat showed that the lard adulteration peak could be distinctly identified. Using this method, a detection limit of 1% lard/randomized lard was reached (P<0.0001).